Mammography Density and Sex Steroid Genes

Institution: University of Southern California
Investigator(s): Sue Ann Ingles, DrPH -
Award Cycle: 2000 (Cycle VI) Grant #: 6IB-0093 Award: $102,328
Award Type: IDEA
Research Priorities
Etiology and Prevention>Etiology: the role of environment and lifestyle



Initial Award Abstract (2000)
Mammograms have been found to be most useful in identifying early existing breast cancers before they become palpable. Mammograms in a woman without breast cancer may also convey useful information as to the woman's future risk of breast cancer. The radiographic appearance of the breast is determined by the relative amounts of fat, connective tissue, and epithelial tissue. On mammograms, fat appears as radiologically lucent (clear) areas, whereas connective and epithelial tissue on the mammogram appear as darker areas on the x-ray film. The extent of these mammographic densities has been found to be strongly predictive of breast cancer risk.

We know that hormonal status of a woman influences mammographic densities. Menstruating women have higher amounts of densities than women who have undergone menopause. There is also some evidence that women who take postmenopausal hormone replacement therapy have more densities. We therefore hypothesize that genes involved in production of female sex hormones are associated with mammographic density levels. We propose to study the association between mammographic density and genetic variations in these genes in a group of women who have previously been diagnosed with breast cancer.

We will conduct these molecular analyses in 453 White and African American women diagnosed with breast cancer. The genetic variants we are looking for are germline alterations; this means that these women were born with this genetic profile. This genetic profile is not changed by the diagnosis of cancer.

We will also provide preliminary evidence as to whether hormone replacement therapy is more strongly associated with mammographic density in women with one of these specific genetic variants.

If variants in one or more of these genes are associated with mammographic density, this may help us further understand the role of these female hormones in breast cancer etiology. If it turns out that women with specific genetic alterations have very high density levels if they are on hormone replacement therapy, then this could provide preliminary evidence that women with certain specific genetic alterations may be at higher breast cancer risk if they use hormone replacement therapy.


Final Report (2001)
Mammograms (x-ray pictures of the breast) are extremely useful in identifying early breast cancers, before they become palpable. Mammograms in a woman without breast cancer may also convey useful information as to the woman’s future breast cancer risk. The radiographic appearance of the breast in the x-ray picture is determined by the relative amounts of fat, connective tissue, and epithelial tissue. On mammograms, fat appears as radiologically lucent (clear) areas, whereas connective and epithelial tissue on the mammogram (mammographic densities) are darker areas and have been found to be strongly predictive of breast cancer risk.

We know that hormonal status of a woman influences mammographic densities. Menstruating women have higher amounts of densities than women who have undergone menopause. There is also some evidence that women who take postmenopausal hormone replacement therapy have more densities. We therefore hypothesize that genes involved in production of female sex hormones are associated with mammographic density levels. We studied the association between mammographic density and genetic variations in these genes in a group of women who have previously been diagnosed with breast cancer.

We conducted molecular analyses in 453 White and African American women diagnosed with breast cancer. The genetic variants we examined are germline alterations; this means that these women were born with this genetic profile. This genetic profile is not changed by the diagnosis of cancer. We studied the associations between mammographic density and genes involved in the biosynthesis and activity of estrogen and progesterone which have variations known as single nucleotide polymorphisms (SNPs). Specifically, we determined whether mammographic density is associated with known germline polymorphisms in four genes: cytochrome p450c 17( (CYP 17), 17( hydroxy steroid dehydrogenase 1 (HSD17B1), 3? HSD II, and the progestin receptor (PR) gene.

We have some evidence that mammographic density is associated with at least one of these genetic variants. Preliminary results suggest some association with the CYP 17 gene, with slightly higher mammographic density in women with a particular variation, or polymorphism, called the A2 allele. Further data analyses are in progress.

If genetic alterations in one or more of these genes are associated with mammographic density, this may help us further understand the role of endogenous hormones (i.e., natural hormones in the body) in breast cancer etiology. If it turns out that these genes modify the effect of other hormonal risk factors for breast cancer on mammography density, then this may help us ultimately understand which women are at higher breast cancer risk if they use hormone replacement therapy.